Lastly, we demonstrate our model with a live turtlebot3[1]} as the platform.
The turtlebot first creates a map of the area using gmapping[2]}, which is then processed into an observation format recognizable by the agent. The target location is marked on the observation along with the robot's current location.
The agent will produce a command for the robot to go in one of four direction for a set length.
This process repeats until the robot reaches the target location.
Without any fine-tuning, the robot learned to compensate for odometry inaccuracies and drift by performing recovery moves during the navigation, even though it was not exposed to this drift during the simulated training.
Our robot is able to successfully complete the task in multiple locations, a screen capture of the demonstration video is shown in figure.
REF .
